Exponential smoothing model is one of the main load forecasting models of power systems, the accuracy of the model depends on smoothing coefficient. In this paper, a study on how to seek the best smoothing coefficient is given. The results show that using the principle of weighting more on near data and weighting less on far data to seek the optimal smoothing coefficient can get a better result. Based on the result, a method of how to weight more on near data and weight less on far data is proposed. A practical example of load forecasting with the method is also shown here.

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This paper introduces a new strategy for power systems harmonics analysis based on N=L×10 M -point DFTs. When the fundamental frequency of a power system signal is 50 Hz, a sampling frequency 2000Hz is selected, N=L×10 M -point DFTs can reduce spectral leakage and obtain high accuracy harmonic parameters. The simulation results in MATLAB show that the strategy are feasible, and comparing with the harmonic analysis method based N=2 M -point DFTs in radix-2 or radix-4 FFT algorithm, the harmonic analysis method based N=L×10 Mpoint DFTs has the obvious superiority. This new strategy maybe open up a new ideas for power system harmonic analysis.